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Application of Big Data Fusion Based on Cloud Storage in Green Transportation: An Application of Healthcare.
- Source :
-
Scientific Programming . 6/29/2020, p1-8. 8p. 1 Color Photograph, 4 Diagrams, 2 Charts. - Publication Year :
- 2020
-
Abstract
- In the 21st century, transportation brought great convenience to people, but at the same time, automobile transportation is the major factor causing greenhouse gas emissions and climate change. Movements of the world towards green environments, there is hike in use and production of electric vehicles (energy vehicles). However, with the continuous growth in the number of energy vehicles, it is necessary for the government to provide strong support in the construction of charging piles. Real-time and effective management has become a practical problem for the relevant departments which needs to be solved. This paper uses the information research method to fuse the huge amount of heterogeneous data generated by the charging pile resultant to the new energy electric vehicle in the vehicle network and introduces cloud computing as its storage module to facilitate the storage and related expansion of the big data. This paper proposes a system scheme of heterogeneous data fusion based on cloud computing for the acquisition, storage, and fusion of heterogeneous data in the vehicle network. After testing the results, it shows that the system is stable and effective in practical application, which can meet the design requirements of the system. What is the significance of analyzing big data of charging point? Considering from the supply side, obtaining the user's charging behaviour data is helpful to build a digital map of the charging pile of new energy vehicles, connect the service information between the vehicle enterprises and the charging pile enterprises, and provide the most comprehensive and effective real-time charging information covering the widest range of vehicles, which can solve many problems of information asymmetry in the current charging information service. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10589244
- Database :
- Academic Search Index
- Journal :
- Scientific Programming
- Publication Type :
- Academic Journal
- Accession number :
- 144303689
- Full Text :
- https://doi.org/10.1155/2020/1593946